Traffic speed forecasting by mixture of experts

Traffic speed is one of the most important quantities for travel information systems. Accurate speed forecasting can help in trip planning by allowing travelers to avoid the congested routes, either by choosing the alternative routes or by changing the departure time. It is also helpful for traffic monitoring, control, and planning. An important feature of traffic is that it consists of free flow and congested regimes, which have significantly different properties. Training a single traffic speed predictor for both regimes typically results in suboptimal accuracy. To address this problem, a mixture of experts algorithm which consists of two regime-specific linear predictors and a decision tree gating function was developed. A generalized expectation maximization algorithm was used to train the linear predictors and the decision tree. The proposed algorithm was evaluated on a 5-mile stretch of I35 highway in Minneapolis containing 10 single loop detector stations, with prediction horizons ranging from 5 minutes to one hour ahead. Experimental results showed that the mixture of experts approach outperforms several popular benchmark approaches.

• Record URL:
  https://doi.org/10.1109/ITSC.2011.6083118
• Availability:
  • Find a library where document is available. Order URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6069628
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Coric, V
  • Wang, Zhuang
  • Vucetic, S
• Conference:
  • 14th International IEEE Conference on Intelligent Transportation Systems (ITSC 2011)
  • Location: Washington DC, United States
  • Date: 2011-10-5 to 2011-10-7
• Publication Date: 2011-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 283-288
• Monograph Title: 14th International IEEE Conference on Intelligent Transportation Systems (ITSC 2011)

Subject/Index Terms

• TRT Terms: Algorithms; Field studies; Forecasting; Traffic speed
• Geographic Terms: Minneapolis (Minnesota)
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning; I73: Traffic Control;

Filing Info

• Accession Number: 01565611
• Record Type: Publication
• ISBN: 9781457721984
• Files: TRIS
• Created Date: May 20 2015 2:33PM